MarkView

Important

Project status (August 2026): MarkView is feature-frozen and no longer under active development. It will receive no further updates or releases, but the project remains open source under the MIT license — the code stays available and existing releases keep working as-is. Active development has moved to its successor, Rho MD — a Markdown reader + notebook built on everything we learned here, with interactive documents, a document library, and Android support. Issues and pull requests on this repository may receive limited or no attention. Feature work by the community continues in a fork, which cuts its own releases.

An AI-native Markdown reader for Windows and Linux — renders Mermaid diagrams, KaTeX math, Vega-Lite charts, and GFM tables the way modern LLMs produce them.

Gallery

Data charts (Vega-Lite)	Diagrams (Mermaid)

Math + tables	Release notes view

When to Use

MarkView is a reader, not an editor. Open it when you want to:

• See LLM output rendered immediately — paste a Claude / ChatGPT / Gemini reply that contains Mermaid diagrams or Vega-Lite charts and see them as visuals, not raw JSON / code blocks. No copy-pasting into a separate site.
• Read LLM-generated technical reports — KaTeX math, GFM tables, syntax-highlighted code, and diagrams render in one consistent view.
• Open a .md file and just read it — release notes, README files, docs from a cloned repo. No editor UI in the way.

If you need editing, sync, plugins, or note-taking, Obsidian, Typora, and MarkText are great. MarkView is intentionally read-only and lightweight — no account, no sync, no telemetry.

Download

Warning

Security note for the 1.0.5 builds below. They render raw HTML inside a Markdown document without sanitising it, so opening a .md file you did not write can run script inside the app — and in these builds that script can read local files and send their contents out. The fix (#8) is in main and in the community fork, but no further release will be cut from this repository. If you open Markdown from untrusted sources, take a build from the fork, use Rho MD, or build from main yourself.

Windows

Format	Link
Portable (.exe)	MarkView_v1.0.5_portable.exe
Installer (MSI)	MarkView_v1.0.5_x64.msi

Note: Windows SmartScreen may warn about downloaded .exe / .msi files because they are not code-signed. To bypass: click "More info" → "Run anyway". Alternatively, right-click the file → Properties → check "Unblock" → OK.

Linux

Format	Link	Notes
.deb (1.0.5)	MarkView-1.0.5-amd64.deb	Ubuntu 24.04+, Debian 13+ (uses system WebKit)
.AppImage (1.0.5)	MarkView-1.0.5-amd64.AppImage	Any distro with libfuse2, self-contained

# .deb install
sudo dpkg -i MarkView-1.0.5-amd64.deb

# .AppImage install
chmod +x MarkView-1.0.5-amd64.AppImage
./MarkView-1.0.5-amd64.AppImage

After install, open the About panel and click "Set MarkView as default .md handler" to bind .md files to MarkView system-wide.

Linux Troubleshooting

Symptom	Fix
.AppImage won't launch on Ubuntu 24.04 (error while loading shared libraries: libfuse.so.2)	sudo apt install libfuse2t64
.deb install fails with WebKit dependency error on older Debian / Ubuntu	sudo apt install libwebkit2gtk-4.1-0 (or -4.0-37 on older releases)
"Set as default" doesn't take effect	Run manually: xdg-mime default markview-reader.desktop text/markdown
Snap version can't open files outside home directory	sudo snap connect markview-reader:removable-media (and/or :home)

Community Fork

Feature work on MarkView continues in a community fork — Scorpse/markview (branch main): an AI-native Markdown reader — Mermaid, Vega-Lite, KaTeX, Graphviz/DOT, D2, Markmap, WaveDrom, Marp slides, plus JSON/YAML/JSONL/CSV/config viewers.

It is MIT like this repository and maintained independently by @Scorpse. New releases and binaries come from there — this repository cuts none — so issues about those builds belong in that fork.

Features

• Mermaid diagrams — Flowchart, sequence, state, class, ERD, gantt, pie, mindmap, timeline, journey. Each type code-splits on demand.
• Vega-Lite charts — Bar, line, scatter, heatmap, candlestick, stacked area. Any data spec an LLM can emit as JSON renders as SVG.
• KaTeX math — Inline and block, matrices, integrals, series.
• GFM — Tables, task lists, footnotes, strikethrough, autolinks.
• Syntax highlighting — 100+ languages via highlight.js.
• Table of Contents — Auto-generated from headings with scroll spy.
• Folder Browser — Browse a directory tree of .md files.
• In-Document Search — Ctrl+F with highlight and navigation.
• Dark / Light Theme — Follows system preference or manual toggle. Charts re-render with theme-aware colors on switch.
• Font Size Control — Adjustable (12–28 px), persisted.
• File Watching — Auto-reloads when the file is modified externally.
• Drag & Drop — Drop .md files directly into the window.
• Default .md Handler — One-click "Set as default" on both platforms (Windows: auto-registers via registry; Linux: xdg-mime default).
• Recent Files — Last 10 opened files on the welcome screen.
• Print — Clean print output (content only).
• Token Estimation — Document stats with word count and estimated token count.

Keyboard Shortcuts

Shortcut	Action
Ctrl+O	Open file
Ctrl+W	Close current tab
Ctrl+Tab / Ctrl+Shift+Tab	Next / previous tab
Ctrl+F	Search in document
Ctrl+B	Toggle sidebar (TOC / folder browser)
Ctrl+P	Print
Ctrl+Shift+T	Toggle light / dark theme
Ctrl+= / Ctrl+- / Ctrl+0	Font size: increase / decrease / reset

Tech Stack

• Tauri 2 (Rust) — Desktop framework (WebView2 on Windows, WebKit2GTK on Linux)
• React 19 + TypeScript — Frontend UI
• Vite 6 — Build tooling
• TailwindCSS 4 — Styling
• Zustand — State management
• Unified/Remark/Rehype — Markdown processing pipeline

How This Project Was Built

MarkView was born from a controlled experiment: does the format of a specification affect the quality of LLM-generated code?

We wrote the same app spec in three formats — Natural Language (NL), STL, and STLC — and gave each to a separate Google Gemini instance. Same 19 features, same tech stack, same prompt. The results:

Metric	Natural Language	STL	STLC
Feature Completion	8.5/19 (45%)	13/19 (68%)	10/19 (53%)
Compiles?	NO	YES	YES
Fully Autonomous?	NO	YES	NO
Human Interventions	1+	0	1

STL was the only format that compiled on the first attempt with zero human intervention. The NL version didn't even compile (missing build.rs, broken regex). The STLC version compiled but missed practical details like CSS imports — correct logic, broken visuals.

The Process

1. Planning (Claude) — Claude wrote the full application specification in STL format (plan_stl.md), encoding every feature, component, and dependency as typed semantic edges with explicit confidence scores.

2. Implementation (Gemini) — The STL plan was passed to Google Gemini, which generated the complete working codebase — Rust backend, React frontend, styling, and configuration — autonomously in a single pass.

What Is STL?

STL (Semantic Tension Language) encodes knowledge as typed, weighted semantic edges:

[MarkView] -> [Markdown_Reader] ::mod(
  rule="definitional",
  confidence=0.99,
  intent="Render .md files into beautifully typeset documents for reading (not editing)"
)

Each edge carries:

• rule — relationship type (causal, definitional, empirical, logical)
• confidence — certainty level (0.0–1.0). 0.99 = hard requirement. 0.7 = nice to have.
• intent — what this actually means in context

Natural language buries priorities between the lines. STL makes them explicit — and transferable between any AI model (Claude, Gemini, GPT) with near-zero information loss.

Learn more about STL at stl-lang.org — source and spec on GitHub.

Development

cd markview
npm install
npm run tauri dev

Build

npm run tauri build

License

MIT — © 2026 Wuko-Syn DEV / scos-lab. Free to use, fork, and modify.

Developed by

SCOS-LAB